DNA amplification methods provide a powerful and widely used tool for genomic analysis. Polymerase chain reaction (PCR) methods, for example, permit quantitative analysis to determine DNA copy number, sample source quantitation, and transcription analysis of gene expression. High resolution melt (HRM) analysis is an important tool used for characterization of amplification products, by way of example, for genotyping, mutation screening, methylation analysis or to ensure that the intended product was amplified. Various HRM curve methods may allow for the detection of single base changes in specific regions of the genome, such as single nucleotide polymorphisms (SNPs). SNP analysis and other techniques facilitate the identification of mutations associated with specific diseases and conditions, for example, but not limited by, various cancers, thalassemia, neonatal diabetes, and rheumatoid arthritis. Melt curve analysis can indicate if multiple products are amplified, non-specific amplification has occurred or if there were assay amplification issues such as primer-dimmer formation. High resolution melt analysis can also be useful for the analysis of other biological samples including but not limited by proteins to analyze the signal changes within a sample, or between samples with changing temperature.
Statistical assay variations in melt curve data may result from system noise in an analysis system, such as the thermal non-uniformity of a thermocycler block in a thermal cycler apparatus. For certain applications, the melting point shift between samples may be only fractions of a degree. In the case of SNP analysis, the SNP mutations may shift the melting point temperature by no more than 0.2° C. Providing methods for analysis of such data is tantamount to providing the analyses mentioned in the above. Additionally, providing a method for which a control sample is not required in order to make an identification of a sample may provide enhanced quality of the identification made. Such methods yielding a sample identification in which a control is not required may be more robust by, for example, but not limited by, avoiding the misidentification of a control sample, or by interference caused by contaminants in a control sample.
Accordingly, there is a need in the art for methods of analyzing small differences in melting curves in the presence of the inherent noise of the analysis, which methods may additionally provide enhanced quality of identification by utilizing unbiased processes not requiring a control.